TL;DR
The proposed Multi-Objective Narwhal Optimizer (MONO), a Pareto-based extension of the recently developed Narwhal Optimizer, incorporates Pareto dominance, external archive management, adaptive multi-leader guidance, and crowding-distance-based diversity preservation to effectively balance convergence and exploration throughout the search process.
Experimental results show that MOAEO achieves competitive convergence and diversity across multiple benchmark suites, and highlights MOAEO’s potential as an effective approach for solving complex multi-objective optimization problems.
This work presents an enhanced multi-objective dung beetle optimization algorithm that is implemented to tackle the multi-objective path planning optimization problem for mobile robot, and numerical simulation results verify that the method achieves sound performance in resolving practical engineering issues.
A dynamic two-population co-evolutionary algorithm (CHEA), which balances feasibility, convergence and diversity at different stages by dynamically adjusting the number of offspring of the two populations by dynamically adjusting the number of offspring of the two populations.
A novel evolutionary algorithm termed CMOEA-TSD is proposed, which adopts a three-population, two-stage co-evolutionary framework to enhance diversity and coordinate multiple search behaviors and significantly outperforms seven state-of-the-art algorithms.
This study introduces Multi-Objective Chaos Game Optimization (MOCGO), a metaheuristic algorithm developed for the purpose of handling multi-objective structural optimization problems with constraints that performs significantly better than other algorithms, including NSGA-II, MOGOA, MOALO, and MOAVOA.
Multi-objective optimization plays an important role in modern design and complex engineering applications. However, achieving an effective balance between the convergence and diversity of Pareto-optimal solutions remains challenging. This paper proposes a Sobol-driven Multi-objective Whale Migration Algorithm (SMOWMA)...
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